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Estimating the positions of sensor nodes precisely is one of the major tasks in Wireless Sensor Networks (WSN). Due to the limited hardware resources and the energy capacity it is necessary to develop energy-aware localization algorithms. Here we present a new technique to convert the complex non-linear least squares calculation and distribute the tasks over the network effectively. Our proposed algorithm...
An ARMA(p,q) model parameterization method is outlined and proposed for approximating the Clarke's theoretical autocorrelation function. The method uses a strategy that consists of computing the AR coefficients in a preliminary stage and then, in a subsequent stage, computing the MA coefficients. In the first stage it considers a "redesigned" least squares modified Yule Walker equations...
The parameter estimations are unstable when the determinant of the coefficient matrix of the normal equation is closed to 0 in least-squares estimation. The deviation of estimator is too great because of rounding error of calculator and it is hard to get the precise inverse of the coefficient matrix. A matrix function which is matrix power series was introduced in proposed method based on ridge estimation...
Time-varying systems and nonstationary signals arise naturally in many engineering applications, such as speech, biomedical, and seismic signal processing. Thus, identification of the time-varying parameters is of crucial importance in the analysis and synthesis of these systems. The present time-varying system identification techniques require either demanding computation power to draw a large amount...
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